High-Dimensional Additive Hazards Regression for Oral Squamous Cell Carcinoma Using Microarray Data : A Comparative Study
Joint Authors
Tapak, Lily
Sadeghifar, Majid
Hamidi, Omid
Jafarzadeh Kohneloo, Aarefeh
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-05-19
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Microarray technology results in high-dimensional and low-sample size data sets.
Therefore, fitting sparse models is substantial because only a small number of influential genes can reliably be identified.
A number of variable selection approaches have been proposed for high-dimensional time-to-event data based on Cox proportional hazards where censoring is present.
The present study applied three sparse variable selection techniques of Lasso, smoothly clipped absolute deviation and the smooth integration of counting, and absolute deviation for gene expression survival time data using the additive risk model which is adopted when the absolute effects of multiple predictors on the hazard function are of interest.
The performances of used techniques were evaluated by time dependent ROC curve and bootstrap .632+ prediction error curves.
The selected genes by all methods were highly significant (P<0.001).
The Lasso showed maximum median of area under ROC curve over time (0.95) and smoothly clipped absolute deviation showed the lowest prediction error (0.105).
It was observed that the selected genes by all methods improved the prediction of purely clinical model indicating the valuable information containing in the microarray features.
So it was concluded that used approaches can satisfactorily predict survival based on selected gene expression measurements.
American Psychological Association (APA)
Hamidi, Omid& Tapak, Lily& Jafarzadeh Kohneloo, Aarefeh& Sadeghifar, Majid. 2014. High-Dimensional Additive Hazards Regression for Oral Squamous Cell Carcinoma Using Microarray Data : A Comparative Study. BioMed Research International،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-468595
Modern Language Association (MLA)
Hamidi, Omid…[et al.]. High-Dimensional Additive Hazards Regression for Oral Squamous Cell Carcinoma Using Microarray Data : A Comparative Study. BioMed Research International No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-468595
American Medical Association (AMA)
Hamidi, Omid& Tapak, Lily& Jafarzadeh Kohneloo, Aarefeh& Sadeghifar, Majid. High-Dimensional Additive Hazards Regression for Oral Squamous Cell Carcinoma Using Microarray Data : A Comparative Study. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-468595
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-468595